U.S. patent application number 13/453856 was filed with the patent office on 2012-11-01 for systems and methods for improved ophthalmic imaging.
This patent application is currently assigned to Carl Zeiss Meditec, Inc.. Invention is credited to Scott A. Meyer, Harihar NARASIMHA-IYER.
Application Number | 20120274897 13/453856 |
Document ID | / |
Family ID | 46052726 |
Filed Date | 2012-11-01 |
United States Patent
Application |
20120274897 |
Kind Code |
A1 |
NARASIMHA-IYER; Harihar ; et
al. |
November 1, 2012 |
SYSTEMS AND METHODS FOR IMPROVED OPHTHALMIC IMAGING
Abstract
Systems and methods for improving ophthalmic imaging by
correlating the location of a measurement on the pupil of the eye
with a quality of the measurement and further controlling
subsequent measurements based on the quality are presented. Aspects
of the invention include obtaining optical coherence tomography
(OCT) measurements through cataracts or other media opacities,
obtaining B-scans with minimized tilt, and automated OCT data
acquisition of select structures in the eye. Embodiments of the
invention directed towards imaging tissues with angle dependent
layer contrast and mapping the size and location of cataracts in
the eye are also described.
Inventors: |
NARASIMHA-IYER; Harihar;
(Livermore, CA) ; Meyer; Scott A.; (Livermore,
CA) |
Assignee: |
Carl Zeiss Meditec, Inc.
Dublin
CA
|
Family ID: |
46052726 |
Appl. No.: |
13/453856 |
Filed: |
April 23, 2012 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61479788 |
Apr 27, 2011 |
|
|
|
61536776 |
Sep 20, 2011 |
|
|
|
Current U.S.
Class: |
351/206 ;
351/205; 351/246 |
Current CPC
Class: |
A61B 3/102 20130101;
A61B 3/12 20130101; A61B 3/117 20130101; A61B 3/152 20130101; A61B
3/113 20130101 |
Class at
Publication: |
351/206 ;
351/205; 351/246 |
International
Class: |
A61B 3/14 20060101
A61B003/14; A61B 3/10 20060101 A61B003/10 |
Claims
1. A method to obtain ophthalmic measurement data, the method
comprising: collecting a plurality of measurements at different
entry locations on the pupil of a subject, wherein there is a
relationship between the coordinates of the measurement system and
the pupil entry location; determining a representative value for
each measurement that characterizes a quality of the measurement;
identifying the best representative value and its corresponding
pupil entry location; and controlling the measurement system to
acquire subsequent measurements at the pupil entry location
corresponding to the best representative value determined.
2. A method as recited in claim 1, wherein the plurality of
measurements are OCT A-scans.
3. A method as recited in claim 2, wherein the quality of the
measurement is the signal to noise ratio.
4. A method as recited in claim 3, wherein the best representative
value is the value with the highest signal to noise ratio.
5. A method as recited in claim 1, wherein the plurality of
measurements are OCT B-scans
6. A method as recited in claim 5, wherein the quality of the
measurement is the tilt of the B-scan.
7. A method as recited in claim 6, wherein the best representative
value is the value with the least amount of tilt.
8. A method as recited in claim 1, further comprising correcting
for movement of the retina.
9. A method as recited in claim 1, wherein the quality of the
measurement is the intensity of the signal.
10. A method as recited in claim 1, wherein the plurality of
measurements are taken in the posterior part of the eye.
11. A method as recited in claim 1, wherein the plurality of
measurements are taken in the anterior part of the eye.
12. A method as recited in claim 1, wherein the subsequent
measurements are taken at a follow-up visit.
13. A method as recited in claim 1, where in the pupil entry
location is chosen to optimize the visualization of a particular
structure in the eye.
14. A method as recited in claim 1, where in the pupil entry
location is chosen to avoid media opacities.
15. A method as recited in claim 1, wherein the pupil entry
location is determined and controlled using an image of the eye
containing the pupil.
16. A method as recited in claim 1, wherein the best representative
value is identified from representative values characterizing more
than one quality of the measurement.
17. A method as recited in claim 1, wherein the best representative
value is identified by a user based on a display of the
representative values.
18. A method as recited in claim 1, wherein the pupil entry
location is chosen to optimize the visualization of abnormalities
at the anterior surface of the retina.
19. A method as recited in claim 1, further comprising adjusting
the pupil entry location to account for pupil constriction and
dilation
20. A method of collecting image data of an eye of a patient using
an ophthalmic imaging system, said imaging system including a
scanner for directing a beam of radiation through the pupil, said
method comprising: selecting a preferred location on the pupil for
the entry of the beam of radiation; monitoring the motion of the
eye; and adjusting the positioning of the beam of radiation in
response to the monitored motion to maintain the preferred pupil
entry location while capturing image data of structures within the
eye.
21. A method as recited in claim 20, wherein the ophthalmic imaging
system is an optical coherence tomography (OCT) system.
22. A method as recited in claim 21, wherein the step of monitoring
the motion of the eye includes imaging the pupil with an imaging
system and determining the location of the pupil from within the
image.
23. A method as recited in claim 22, wherein the selected pupil
entry location is the center of the pupil.
24. A method as recited in claim 22, wherein the pupil entry
location is selected by the user.
25. A method as recited in claim 22, wherein the pupil entry
location is selected and maintained based on the boundaries of the
pupil identified in the image.
26. A method as recited in claim 22, wherein the pupil entry
location is adjusted to account for pupil constriction and
dilation.
27. A method as recited in claim 22, wherein the selected pupil
entry location is the same location as measurements acquired at a
previous examination of the patient.
28. An automated method for evaluating tissue in Optical Coherence
Tomography (OCT) images of the eye, the method comprising:
acquiring intensity data from multiple OCT B-scans of the eye, said
B-scans being taken at two or more different angles of incidence
relative to tissue in eye; processing the intensity data to
identify the differences in the data due to the difference in
angles of incidence; and storing or displaying the identified
differences.
29. A method as recited in claim 28, wherein said step of
processing the intensity data includes registering images derived
from the intensity data at different angles of incidence and
generating an image which displays the differences in intensity
data.
30. A method as recited in claim 28, wherein said step of
processing the intensity data includes determining tissue
characteristics based on the identified differences.
31. A method as recited in claim 30, wherein said tissue
characteristic is a layer thickness.
32. A method as recited in claim 28, wherein said step of
processing the intensity data includes evaluating the intensity
data to determine a scattering profile as a function of depth.
33. A method to analyze opacities in the eye of the patient said
method comprising: collecting a plurality of measurements at
different entry locations on the pupil of a subject, wherein there
is a relationship between the coordinates of the measurement system
and the pupil entry location; determining a representative value
for each measurement that reflects a quality of the opacity; and
displaying or storing the collection of representative values.
34. A method as recited in claim 33, wherein the opacity is a
cataract.
35. A method as recited in claim 34, wherein the quality of the
opacity is density.
36. A method as recited in claim 32, wherein the collection of
representative values is compared to representative values
determined at a different examination of the patient.
37. A method of collecting 3D image data of an eye of a patient
using an optical coherence tomography (OCT) system, said OCT system
including a scanner for directing a beam of radiation through the
pupil and a processor for analyzing OCT data, said method
comprising the steps of: obtaining a series of measurements with
the OCT system wherein the beam of radiation is directed to enter
the pupil at different locations; comparing the quality of the
series of measurements in the processor to determine the optimum
pupil entry location; capturing 3D image data of structures within
the eye with the radiation beam being positioned at the determined
optimum pupil entry location; and storing or displaying the 3D
image data.
38. A method as recited in claim 37, wherein the optimum pupil
location is based upon a determination of the highest signal to
noise ratio.
39. A method as recited in claim 37, wherein the optimum pupil
location is based upon obtaining the least amount of tilt in the
structure of the eye being imaged.
40. A method as recited in claim 37, wherein the optimum pupil
location is based upon avoiding opacities in the eye.
41. A method as recited in claim 37, wherein the pupil entry
location controlled using an image of the eye containing the
pupil.
42. An ophthalmic diagnostic system for obtaining measurement data
at a precise location on the pupil of an eye, said system
comprising: a measurement system comprising a light source to
generate a beam of radiation, said measurement system including
optics for adjusting the entry position of the beam on the pupil of
the eye and for scanning the beam over a set of transverse
locations within the eye, said measurement system further including
a detector for measuring radiation returning from the eye, the
detector generating output signals in response thereto; an imaging
system for capturing images of the pupil; and a processor for
comparing the images from the image system to determine motion of
the eye and for adjusting the beam of radiation in response to the
monitored motion to maintain the preferred pupil entry position
while collecting measurement data.
43. A system as recited in claim 42, wherein the measurement system
is an optical coherence tomography (OCT) system.
44. A system as recited in claim 43, wherein the pupil entry
location is the center of the pupil.
45. A system as recited in claim 43, wherein the pupil entry
position is selected by the user.
46. A system as recited in claim 43, said processor further
selecting and maintaining the pupil entry location based on the
boundaries of the pupil identified in the image.
47. A system as recited in claim 43, said processor further
determining an optimal pupil entry position based on a quality of
the measurement data.
48. A system as recited in claim 43, said processor further
determining the pupil entry position based on measurement data
collected at a previous examination of the eye.
Description
PRIORITY
[0001] This application claims priority to U.S. Provisional
Application Ser. No. 61/479,788, filed Apr. 27, 2011, and U.S.
Provisional Application Ser. No. 61/536,776, filed Sep. 20, 2011,
both of which are hereby incorporated by reference.
TECHNICAL FIELD
[0002] One or more embodiments of the present invention relate
generally to improvements in the quality of data acquisition in
ophthalmic diagnostic systems. In particular, it is an object of
the present invention to automate the process of finding the best
position to take optical coherence tomography measurements as well
as maintaining that position over the acquisition time to ensure
that the optimal signal for a particular type of measurement is
obtained and maintained, allowing measurements to be taken
automatically, without user intervention, and in the presence of
media opacities. Embodiments related to imaging tissues with angle
dependent reflectivity are also considered.
BACKGROUND
[0003] In optical coherence tomography (OCT) imaging, effort is
placed on obtaining high image quality to allow for reproducible
and clear visualization of structures and pathologies as well as
quantitative measurements of features and layers within the eye.
Typically OCT measurements of the posterior section of the eye are
made with the focus of the beam in the plane of the pupil and the
beam entering through the center of the pupil. In theory this
allows the largest possible entry and exit pupil, allowing for
optimal collection of the OCT signal as well as any additional
signals used for alignment purposes. The resulting retinal image
shows bands of varying reflectivity signals that have been
correlated to layers identified in histology. Segmentation of the
retinal tissue is typically made based on the observed reflectivity
differences between layers, although information about the expected
configuration of the layers may also be used. It has recently been
recognized that the reflectivity of some structures in the eye may
depend on the local tilt of the retina relative to the OCT
beam.
[0004] Although a central entry point is nominally optimal, there
are a number of reasons to use entry points that are not central.
In subjects with media opacities such as cataracts, the measurement
beam may not pass well through the opacity. In such cases, it is
sometimes possible to steer the measurement beam through a
different entry position so that the opacity is avoided. In other
subjects, the shape of the eye may be such that the image of the
retinal tissue appears tilted. A different entry point in the pupil
may result in a flatter image. Because layer measurements are
typically made along A-scans, a flatter retina may result in
measurements with less geometrical error. Furthermore, since many
OCT systems have decreasing signal quality further from the zero
delay, a flatter retina may have better uniformity of intensity
across the B-scan. Finally, some tissues in the eye have
reflectivity that depends on the angle of incidence. Ensuring a
flat retina on each visit reduces the variance of incidence angle
over multiple visits, which reduces the impact of directional
reflectivity on the variability of measurements made on the image.
Alternately, optimal imaging of tissues with strong directional
reflectivity may require a specific angle of incidence which by
geometry requires a different pupil entry location, or may even
require scans with multiple angles of incidence (and therefore
multiple pupil entry locations) to be combined prior to layer
detection.
[0005] In current systems, the user has to manually adjust the
pupil entry position and find the "best" entry position for the
particular subject and imaging application by a trial and error
method. This is a subjective procedure, in which the operator has
to review the OCT scan, the fundus image, and the iris image in
order to determine the alignment that results in an optimal
compromise between OCT signal quality, B-scan tilt, and fundus
image quality. Though it is not current practice, in the future
users may also wish to optimize based on the specific reflectivity
profile of given layers.
[0006] Once the best position is identified, it is still difficult
to maintain the entry position for the duration of the scan because
of eye motions or changes in gaze. This effect is particularly
important in OCT systems where the scans usually take a few seconds
and a dense cube of data is acquired.
[0007] Various attempts have been made to increase feedback to the
operator and automate aspects of data acquisition to achieve the
highest quality images possible. Retinal tracking systems have been
described (see for example US Patent Publication No. 2005/0024586,
U.S. Pat. No. 7,480,396 and U.S. Pat. No. 7,805,009, and U.S.
patent application Ser. No. 13/433,127, filed Mar. 28, 2012, hereby
incorporated by reference) to compensate for motion of the retina
during retinal imaging. However, retinal tracking methods usually
work by analyzing images of the back of the eye that are mostly
obtained by point scanning or line scanning devices that also
depend on an optical path that goes through the pupil. If the scan
entry position is not optimal, the images used for tracking the
retina will also be affected, resulting in poor quality of tracking
or a total failure to track if the fundus image quality degrades
significantly.
[0008] It is therefore an object of the current invention to
address some of the limitations described above. In particular, it
is an object of the present invention to automate the process of
finding the best position to take OCT measurements as well as
maintaining that position over the acquisition time to ensure that
the optimal signal is obtained and maintained, allowing
measurements to be taken automatically and without user
intervention. This invention further makes it possible to have a
set of scan patterns optimized for different structures in the eye
and allows the system to automatically place the beam at the
optimal angle for each scan pattern. The information from the scans
taken at multiple locations through the pupil can also be combined
to produce a comprehensive view of the eye. The invention further
makes it possible to ensure that a scan acquired on a future visit
is acquired with the same pupil entry position, reducing any effect
that variability of pupil entry location has on the variability of
image quality or on variability of quantitative measurements.
SUMMARY
[0009] The invention described herein relates to a system and
method to improve the visualization of different structures in the
eye using a new acquisition strategy. The invention addresses the
problems described above and includes methods that could fully
automate the data acquisition process even for subjects with media
opacities while also helping to improve the quality of the
ophthalmic images. A further aspect of this invention is to propose
methods to optimize the data acquisition for specific structures in
the eye depending on the anatomy. Embodiments of the invention
directed towards imaging tissues with angle dependent layer
contrast and mapping the size and location of cataracts in the eye
are described.
[0010] One aspect of the invention is correlating the pupil
location associated with a particular OCT measurement with the
quality of that measurement. This correlation has many potential
applications including three that will be described in detail
below: imaging through cataracts and other media opacities,
creating automated scan algorithms to image particular locations in
the eye, and obtaining low tilt B-scans. It will be readily
appreciated by someone skilled in the art that the basic components
of the invention would have other possible embodiments that would
fall within the scope of the invention.
[0011] The main components of the pupil tracking system described
herein are illustrated in FIG. 1 and are briefly discussed here.
The system includes an imaging system 101 to obtain an image of a
portion of the eye 103, a processing unit to identify a feature in
the image (pupil detection unit 104), a system to follow the eye
location in (x,y,z) over time (pupil location tracking 105), a
measurement unit 102, and a measurement quality determining unit to
determine the optimized measurement location 106. It is assumed
that the measurement system and imaging system are calibrated so
that the relationship between them is known. In the preferred
embodiment, the anterior portion of the eye is imaged, the feature
is the pupil, and the location of the eye is tracked using a series
of the images. The measurement system of the preferred embodiment
is optical coherence tomography (OCT). It is to be appreciated that
other systems or combinations of systems could fall within the
scope of the invention. The systems and methods described herein
could be implemented automatically or via input from an instrument
operator.
[0012] A first aspect of the invention is to obtain optimal signals
from an ophthalmic measuring device in the presence of cataracts
and other media opacities. As the first step, an image including
the pupil of the eye is collected. Next the boundaries of the pupil
are segmented. Using the segmentation of the pupil, it is possible
to direct the measurement beam to pass through different points on
the pupil. The resulting signals can be analyzed to find the best
position on the pupil to make measurements. This can be achieved by
looking at the characteristics of the returned measurement signal
(such as strength or quality of the returned A-Scans for OCT). Once
the best position is determined, the pupil location tracking will
maintain the measurement beam location of the particular position
on the pupil to continue acquiring the optimal measurement signal
even in the presence of movement or changes in gaze. This can be
accomplished with any type of pupil segmentation and gaze tracking.
While this embodiment is directed towards selecting a specific
pupil entry position based on a quality of the measurement data,
the methods can be generalized to maintain any measurement beam
location including the center of the pupil, a user selected pupil
location, or a pupil location that is the same as that of a prior
scan.
[0013] A further aspect of the present invention is to use the tilt
of the B-scan as a quality metric for a series of measurements on
different locations on the pupil. In so doing, a pupil location
with minimal tilt can be selected and tracked during an OCT
measurement.
[0014] Another aspect of the present invention is the ability to
control the angle of the measurement beam based on a particular
structure of which a measurement is desired. By changing the
location of the measurement beam on the pupil, it is possible to
make the measurement beam go at various angles to the optical axis
thereby making the measurement beam perpendicular to different
structures in the eye. This results in better visualization of
different structures that are sensitive to the orientation of the
measurement beam relative to the surface. The pupil location
tracking unit allows tracking the motion of the patient and hence
obtaining the scans at different angles reliably. Further because
of the pupil location tracking, it will be possible for the system
to keep track of the different angles with which the images were
obtained and potentially build a composite image that includes
information from the different scans.
BRIEF DESCRIPTION OF FIGURES
[0015] FIG. 1 shows a block diagram of a pupil tracking system of
the present invention.
[0016] FIG. 2 is an image of the anterior of the eye that can be
used in the present invention.
[0017] FIG. 3 shows the basic components of an SD-OCT system that
could be used to acquire measurement data in various embodiments of
the present invention.
[0018] FIG. 4 shows a segmentation of the pupil in an image of an
eye.
[0019] FIG. 5 shows one scanning pattern applicable to the present
invention.
[0020] FIG. 6 shows an alternative scanning pattern applicable to
the present invention.
[0021] FIG. 7 illustrates how the present invention can be used to
maintain the location of an ophthalmic diagnostic system in the
presence of movement of the pupil of the eye.
[0022] FIG. 8 illustrates how pupil constriction can lead to
problems in collecting images in the same location over time.
[0023] FIG. 9 shows one approach to dealing with the problem of
pupil constriction while attempting to maintain the same pupil
entry location in subsequent measurements of the eye.
[0024] FIG. 10 shows an alternative approach to dealing with the
problem of pupil constriction while attempting to maintain the same
pupil entry location in subsequent measurements of the eye.
[0025] FIG. 11 illustrates how the pupil entry position can affect
the tilt of the retina in the resulting B-scans acquired at each
location.
[0026] FIG. 12 illustrates how segmentations of the images in FIG.
11 can be used to generate binary masks useful for characterizing
the tilt in the data.
[0027] FIG. 13(a) and (b) show the angle dependent layer contrast
that can result when two B-scans are taken at different angles of
incidence.
[0028] FIG. 14 shows how the measurement system can be translated
relative to the eye of a patient to achieve different measurement
and hence different angle of incidence imaging.
[0029] FIG. 15 shows one way to compare the intensities of B-scans
taken at different angles of incidence.
[0030] FIG. 16 shows an alternative way to compare the intensities
of B-scans taken at different angles of incidence by subtracting
one of the intensities from the other.
[0031] FIG. 17 shows another alternative way to compare the
intensities of B-scans taken at different angles of incidence by
subtracting one of images from the other.
[0032] FIG. 18 shows another alternative way to compare the
intensities of B-scans taken at different angles of incidence by
subtracting one of images from the other in the opposite order of
the subtraction in FIG. 17.
[0033] FIG. 19 illustrates how opacity of the eye can be visualized
using an embodiment of the present invention.
DETAILED DESCRIPTION
[0034] The invention described herein is directed towards improving
ophthalmic imaging by correlating the location of a measurement on
the pupil of the eye with a quality of the measurement and further
controlling subsequent measurements based on the quality. This has
several important applications in the field of ophthalmic imaging
including imaging through cataracts or other media opacities,
obtaining B-scans with minimized tilt, and automated data
acquisition of select structures in the eye. The invention could
result in significantly better data acquisition as well as improved
ease of use for the operator. Each application will be described in
detail below.
[0035] While the invention described herein is applicable to any
ophthalmic diagnostic device that needs to send a measurement
signal into the eye and record the results, the preferred
embodiments described herein will be focused on the field of
Optical Coherence Tomography (OCT). OCT is a non-invasive, in-vivo
imaging technique that is based on the back-scatter or reflectivity
of light in a medium. OCT is particularly valuable in ophthalmic
examinations, where the beam of light produced by the OCT device
scans the eye through the pupil and the image formation process
records the back-scattering profile of the light at each location.
The intensity of the back-scattered light is indicative of the
scattering properties of the tissue and tissue boundaries, and a
grayscale cross-sectional image is formed as the light beam sweeps
across the field of view (FOV). OCT imaging has dramatically
advanced ophthalmic diagnostic capabilities and led also to better
understanding of ocular anatomy. It is an established basis of
routine ophthalmic practice.
[0036] FIG. 1 illustrates a block diagram summarizing the present
invention. Each component will be described in detail below.
[0037] Imaging System
[0038] In the preferred embodiment of the present invention, the
imaging system 101 is responsible for obtaining an image of the
anterior portion of the eye 103. Structures of the anterior part of
the eye such as cornea, pupil and iris will be visible in this
image. The field of view of this image can be variable depending on
the application but should have sufficient field of view to image
the structures mentioned above at a minimum. FIG. 2 shows a sample
image of the front part of the eye that is applicable to the
present invention. The image shows the pupil 201, and iris 202. The
cornea is the overlying transparent structure. These types of
images obtained by the imaging system of the front part of the eye
will be referred to as "iris-images" in the rest of the description
for simplicity.
[0039] In another embodiment of the invention, the imaging system
could also have visible light or infra-red illuminators that can
create reflexes from the anterior part of the eye that are visible
in the image. The location of the reflexes could be segmented and
used for determining the gaze of the eye. In other embodiments of
the invention, the imaging system could also be used to obtain
images of the back portion of the eye. These images could be used
for instance to track the retina and compensate for motion.
[0040] Measurement System
[0041] The measurement system 102 is responsible for obtaining the
measurement of interest. A "measurement" need not be a quantitative
value and could be simply an image but the term measurement is used
to distinguish from the imaging system previously described.
Measurements can be made in various locations in a subject's eye
including the anterior and posterior sections. The invention could
equally be applied to a variety of measurement systems by one
skilled in the art. The measurement system will be spatially
aligned with the imaging system; i.e. the relationship between the
image coordinates of the imaging system and the measurement system
will be well established through calibration procedures. The
measurement system can also be synchronized in time to the imaging
system. For the preferred embodiments described here, the
measurement system is an OCT system. A basic arrangement of the OCT
system is discussed below with reference to FIG. 3. The OCT system
may be configured to obtain images of the posterior pole, with the
OCT beam entering through the pupil. The OCT system may be
configured to obtain images of the anterior segment, with the OCT
beam placed relative to the pupil location. The anterior segment
configuration may be enabled by addition of an external lens, an
internal lens, or the removal of a lens from the posterior imaging
configuration.
[0042] Several implementations of OCT have been developed including
time domain (TD-OCT) and frequency domain (spectral domain (SD-OCT)
and swept-source (SS-OCT)). FIG. 3 shows a basic block diagram for
a spectrometer based SD-OCT system. The light source 300 provides
broad bandwidth light to a short length of an optical fiber 301 to
an input port of a fiber optic coupler 302, which splits the
incoming light beam into the two arms of an interferometer. The two
arms each have a section of optical fiber 303 and 304 that guides
the split light beam from the fiber coupler 302 to the eye of a
patient 305 and a reference reflector 306 respectively. For both
the sample arm and the reference arm, at the terminating portion of
each fiber, there may be a module containing optical elements to
collimate or focus or scan the beam. The returned light waves from
the sample 305 and the reference reflector 306 are directed back
through the same optical path of the sample and reference arms and
are combined in fiber coupler 302. A portion of the combined light
beam is directed through a section of optical fiber 307 from the
fiber coupler 302 to a spectrometer 308. Inside the spectrometer,
the light beam is dispersed by a grating 309 and focused onto a
detector array 310. The collected data is sent to a processor 311
and the resulting processed data can be displayed on a display 312
or stored in memory for future reference and processing. Although
the system of FIG. 3 includes a reflective reference arm, those
skilled in the art will understand that a transmissive reference
arm could be used in its place.
[0043] The interference between the returned light waves from the
sample and reference arms causes the intensity of the combined
light to vary across the spectrum. The Fourier transform of the
interference spectrum reveals the profile of scattering intensities
at different path lengths, and therefore scattering as a function
of depth in the sample (see for example Leitgeb et al., "Ultrahigh
resolution Fourier domain optical coherence tomography," Optics
Express 12(10):2156 2004). The profile of scattering as a function
of depth is called an axial scan (A-scan or A-line). A set of
A-scans measured at neighboring locations in the sample produces a
cross-sectional image (tomogram or B-scan) of the sample. Note that
the principle of operation of a tunable laser based swept source
OCT is very similar to that of a spectrometer based spectral domain
OCT system (see for example, Choma et al. "Sensitivity advantage of
swept source and Fourier domain optical coherence tomography."
Optics Express 11(18): 2183-2189 2003), hence the spectral domain
OCT system for obtaining the 3D image data set can also be a swept
source OCT system or any type of OCT system.
[0044] Pupil Detection Module
[0045] The pupil detection system 104 detects the position of the
pupil in the iris images collected from the imaging system. Many
methods have been proposed to segment the pupil from images of the
eye (see for example Wen-Hung L. et al. "Robust Pupil Detection for
Gaze-Based User Interface" International IUI 2010 Workshop on Eye
Gaze in Intelligent Human Machine Interaction or Zhu et al. "Robust
Pupil Detection using a Curvature Algorithm" Computer Methods and
Programs in Biomedicine 59: 145-157 1999 or Li et al. "Starburst: A
hybrid algorithm for video-based eye tracking combining
feature-based and model-based approaches" Vision for Human-Computer
Interaction Workshop 2005). In one embodiment of this invention,
the eye is illuminated with visible light and so the pupil appears
dark against the comparatively lighter iris region in the collected
image. The dark pupil can be segmented by first finding a dark blob
in the image using intensity based segmentation such as clustering
and connected components. After this step, the algorithm could
optimize for the edges of the detected blob and finally fit a model
to the boundary points. The model could be a simple circle or an
ellipse.
[0046] It is possible to adopt robust methods to fit the selected
model to the boundary points and hence make the segmentation very
accurate. It is not an objective of this invention to propose a new
pupil segmentation method but rather to propose a novel way of
using the segmentation information. Those skilled in the art can
envision using any of a number of described algorithms in the
literature for obtaining the segmentation of the pupil. The
segmentation essentially provides us with coordinates of the center
of the pupil as well as information on the edges of the pupil at
any given point. FIG. 4 shows an example of a segmentation where
the segmentation of the pupil 401 is overlaid on the original iris
image 402.
[0047] Pupil Location Tracking Module
[0048] The pupil location tracking module 105 tracks the location
of the pupil ideally in the lateral (x and y) and axial (z)
directions. In one embodiment, this is accomplished by tracking the
translational pupil position in x and y by comparing the pupil
location in multiple iris images collected from the imaging system.
This information can then be passed back to the measurement system
to re-position the instrument or patient to compensate for the
variation in location. Another embodiment would be a gaze tracking
system that combines the pupil segmentation and segmentation of one
or more corneal reflexes produced from suitably placed visible or
infra-red illuminators on the eye of the patient. These
illuminators could be part of the imaging system and could be
synchronous or asynchronous with the image acquisition. A further
embodiment of the invention would be to combine the pupil tracking
module with a retinal tracking module that can determine the
fixation very accurately. This provides a more accurate
determination of the patient's gaze. These combined tracking
results can be passed to the measurement module to further improve
data acquisition.
[0049] Optimized Measurement Location Determination
[0050] Typically OCT measurements are made by directing the
measurement beam through the center of the pupil as described in US
Patent Publication No. 2007/0291277 hereby incorporated by
reference. In this case an iris viewer was used to aid in the
manual positioning of the OCT treatment beam. A cataract could be
located in the center of the pupil reducing the quality of an OCT
measurement taken at that point. A key aspect of the invention
described herein is to use the fact that different pupil entry
positions give different measurement signals and hence it will be
possible to find an optimal pupil entry position by sampling
different entry positions. Since the pupil segmentation is
available, this can be done automatically and efficiently via an
optimized measurement location determination module 106.
[0051] Consider the sampling pattern of entry positions shown in
FIG. 5. The figure shows a uniform grid of pupil entry locations
503 of lateral (x and y) extend across the pupil of the eye 501.
Let us denote each of these pupil entry locations as PE.sub.i,
where i corresponds to the index of the location. For each of the
pupil entry locations, we can also record the measurement signal.
The corresponding measurement signal is denoted as M.sub.i.
[0052] The optimal pupil entry location can now be determined by
defining an optimality condition on the measurement signal.
PE * = Max i { Q ( M i ) } , ##EQU00001##
[0053] Where Q(.) is a quality function that can be defined for any
type of measurement signal. In words, the best pupil entry location
is the one that gives the best measurement signal. In the example
shown in FIG. 5 the best position is indicated with an arrow 502.
The definition of "best" being defined by the choice of the quality
function Q(.). The framework is general and hence can be used for
any type of measurement signal. For example, if the measurement
system is an FD-OCT system, each measurement signal will be an
A-line.
[0054] For an OCT system with an A-line as the measurement signal,
the quality function may be defined as the Signal to Noise Ratio
(SNR).
Q(M.sub.i)=SNR(M.sub.i)
[0055] The SNR may be calculated based on a very rough segmentation
of the signal from the A-line into signal and noise components. The
SNR can be defined as:
SNR ( M i ) = Mean ( M i signal ) .sigma. ( M i noise ) ,
##EQU00002##
[0056] Where Mean( ) function is the averaging function,
M.sub.i.sup.signal is the useful data in the measurement signal and
M.sub.i.sup.noise is the noise part of the measurement signal.
.sigma.(M.sub.i.sup.noise) is the standard deviation of the
noise.
[0057] This is only one implementation of the invention and those
skilled in the art can define quality functions suited to the
application and the type of measurement signal under consideration.
Additionally, it is not necessary that the sampling pattern used is
a uniform grid. Another possibility is shown in FIG. 6, with a
series of measurements taken along concentric ring scanning
patterns 601. It should be noted that FIGS. 5 and 6 display only
representative scan patterns and the invention is applicable to any
sampling pattern.
[0058] Once the optimal pupil entry position is determined, the
measurement system can acquire data with the desired pupil entry
position. The pupil location tracking system 104 can then be
engaged to track the position of the pupil and hence maintain the
pupil entry location at the optimal location. This position can be
maintained for a single measurement session, throughout a single
visit, or can be recalled for precise positioning of the
measurement beam on repeat or follow-up visits.
[0059] FIG. 7 illustrates how the entry point of the measuring beam
on the pupil is maintained over time. The image on the left shows
the initial position of the eye and the determined "best" pupil
entry position indicated with an arrow 701. The image on the right
shows how the patient's gaze has wandered, and hence the pupil has
moved over time (pupil shifted to right relative to the center of
the eye). However, the pupil location tracking ensures that a lock
is obtained on the optimal pupil entry position 702 to acquire the
data.
[0060] While the methods described in this section are focused on
selecting a specific measurement beam location based on a quality
of the measurement data, the basic concepts can be generalized to
maintain any measurement beam location over time or multiple
visits. This could be the center of the pupil or a location on the
pupil selected by the user. Furthermore, the system could check to
insure that the user selected point lies within the boundaries of
the pupil in order to reduce vignetting that will occur if the beam
width is partially or entirely blocked by the iris.
[0061] One possible issue when trying to image through the same
location of the pupil is that the pupil is inherently changing in
size due to the accommodation of the iris where by it adjusts to
different lighting and external conditions. In such cases the
tracked location might need to be adjusted to ensure that a
measurement is still possible. For example consider the case shown
in FIG. 8, where the pupil constricts between two times, t.sub.1
(left) and t.sub.2 (right). In this case if the original pupil
location 801 is maintained, this will result in no measurement
signal being recorded since the location 802 exists outside the
boundaries of the constricted pupil 803. In cases like this, there
are three options--the first one is to wait till the pupil dilates
so that the same entry position can be maintained.
[0062] In a second option to handle pupil constriction, the optimal
pupil entry location can be scaled with respect to the pupil center
as illustrated in FIG. 9. Suppose the optimal pupil entry location
901 at time t.sub.1 (left image) is at a distance d.sub.1 from the
center of the pupil and at an angle .theta. to the horizontal. Let
the radius of the pupil at that particular angle be R.sub.1. Now
let us consider that the pupil has constricted at time t.sub.2
(right image) and the new radius along the same angle is R.sub.2.
Assuming the pupil is constricting uniformly around the center, the
new optimal position 902 can be found as:
d 2 = d 1 R 1 R 2 . ##EQU00003##
[0063] Here it is assumed that the angle .theta. remains the same
for the new optimal entry position.
[0064] The third option to handle this problem is illustrated in
FIG. 10 for initial pupil entry position 1001 at time t.sub.1. At
time t.sub.2, it is possible to search along the line defined by
angle .theta. from the horizontal and find the point 1002 nearest
to the old position and that lies inside the new boundary of the
pupil.
[0065] Reduced Tilt Measurements
[0066] The entry point of the pupil is related to the incident
angle of the OCT beam on the retina, and as a result, the entry
point is related to the apparent tilt of the retina in the acquired
image. Although for many subjects, the flattest acquired image is
obtained by entering the pupil through the center, the anatomy of
some eyes is such that a flat OCT B-scan may not be obtained at the
center of the pupil, but at some off-center position. A quality
metric can be established to obtain the OCT B-Scans as flat (least
tilt) as possible. Since the OCT signal sensitivity differs based
on the location of the tissue in z, it is highly desirable to have
all the tissue that is being imaged at the same depth or as flat as
possible. As will be described in detail below, another property of
OCT is the change in signal caused due to directional reflectivity
of the different structures being imaged. A flat scan would ensure
that the direction of incidence of the OCT beam is approximately
uniform throughout the scan and thus enables a better comparison
between the reflectance from the different structures.
[0067] It has been seen that the tilt of the B-Scan can be changed
by varying the pupil entry position. (see for example Lujan, et al.
"Revealing Henle's Fiber Layer using Spectral Domain Optical
Coherence Tomography" Investigative Ophthalmology & Visual
Science 52(3) March 2011 1486-1492). FIG. 11 shows B-Scans through
the same location of the retina but at different pupil entry
positions illustrating the tilt effect. FIG. 11(a) shows the
location on the pupil where the OCT image in FIG. 5(b) was
acquired. The resulting OCT B-scan is due to the anatomy of this
eye. We can notice the brighter signal towards the right side of
the B-Scan which is at a higher z-position compared to the left
side of the B-Scan which has a lower signal since it is at a lower
z-position. Note that this is a phenomenon that is seen in most OCT
systems. The signal strength decreases as the distance from the
zero delay increases. In the example shown, the zero delay is at
the top of the B-Scan and hence the signal is expected to be better
at the top (higher z-position) with a roll-off towards the bottom
(lower z-position). This phenomenon is another reason why it is
desirable to obtain the scan with as much reduced tilt as possible
so that the A-Scans are uniform in signal characteristics. As shown
in FIGS. 11(c) and (d) it is possible to obtain a B-Scan with
reduced tilt over the same region by adjusting the pupil entry
position 1102. The intensity across the resulting B-Scan shown in
FIG. 11(d) is much more uniform than the tilted B-Scan in FIG.
11(b).
[0068] In order to find the best pupil entry position in this case,
the measurement signal is defined as single (or multiple) B-Scans
acquired from the same pupil entry position. The B-Scans can then
be quickly segmented to determine the tilt in the B-Scan. The tilt
would be used as the quality metric and the position that minimizes
the tilt can then be selected as the best location for imaging.
[0069] One implementation of determining the tilt is with an
approximate segmentation of the retinal pigment epithelial layer
(RPE), which is usually the brightest layer in the B-Scan. One
method to determine this is to find the brightest signal along each
A-Scan after smoothing to reduce noise. The different segmented
points in the B-Scan are then fit with a line to determine the
general tilt of the B-Scan.
[0070] In another implementation, a segmentation of the structures
of interest might be done based on a calculation of the changes in
the intensity along the scan direction (y gradients) and then
thresholding them, creating a binary image. The binary image can
then be processed to obtain the tilt-angle by fitting a line to the
tissue, such as to either the lower or upper boundary of the tissue
or to a combination of the two locations, such as the center of the
tissue. FIG. 12 shows the binary masks obtained by segmenting the
B-Scans shown in FIG. 11(b) and (d).
[0071] Once the tilt of the B-Scan is determined, the optimal pupil
entry position that gives the desired tilt of the B-Scan can be
selected as the pupil entry position to be used. It has to be noted
that the retinal tracking part of the gaze-tracking system can help
to acquire the B-Scan over the same region of the retina
irrespective of the pupil-entry position. Hence the combination of
the methods described in this invention with a retinal tracking
system of the type described in the commonly owned pending U.S.
application Ser. No. 13/433,127, filed Mar. 28, 2012, allows the
user to acquire data at a particular spot from the retina while
taking advantage of the optimal pupil entry position for the
application of interest.
[0072] Finding the Optimal Pupil Entry Position for Imaging
Different Structures
[0073] The method described in this invention can also be extended
to potentially better visualize different structures in the retina
including but not limited to layers such as Henle's fiber layer,
Retinal Nerve Fiber Layer, different membranes, vitreous
structures, cornea, sub-RPE structures, and the choroid using an
OCT system. This is because different structures are visualized
differently in OCT based on the orientation of the measurement beam
relative to the structure of interest.
[0074] For example, the Henle's fiber layer is visualized the best
when the OCT beam is perpendicular to the fibers in this layer (see
for example Lujan, et al. "Revealing Henle's Fiber Layer using
Spectral Domain Optical Coherence Tomography" Investigative
Ophthalmology & Visual Science 52(3) March 2011 1486-1492).
This is because the directional nature of these fibers produces the
maximum scattering when they are perpendicular to the beam. This
kind of behavior is also true for other layers in the retina such
as the retinal nerve fiber layer.
[0075] When we are trying to visualize a particular region of
interest, using the methods described earlier, we could optimize
for the maximum signal from that layer (given that we know the
approximate location in the A-Scan or B-Scan of the signal of
interest). We could also select the pupil position based on the
geometric orientation that would give the best signal for the
tissue of interest. Furthermore, imaging through the same location
in the pupil at each visit will lead to less variability in the
intensity of any directionally reflective layers that are imaged.
Quantitative segmentations of layers such as the RNFL may be
affected by directional reflectivity, such that variability in
pupil entry point from visit to visit increases the variability in
the quantitative measurements. A common pupil entry point used at
every visit should improve the reproducibility of such
measurements. It is also possible that a quality metric that is a
function of multiple measures of quality could be used (e.g.,
Q=signal to noise ratio times a measure of uniformity, or
SNR*(1-tilt), or that a set of rules for selecting the quality
metric to be optimized could be implemented (e.g., accept up to 3
dB loss of signal in order to obtain a flatter image, but no
more).
[0076] Hence using the methods described in this invention, it will
be possible to select the best pupil entry position for imaging a
particular structure of interest. A detailed description for this
aspect of the invention will now be described.
[0077] Angle Dependent Layer Contrast
[0078] In one embodiment that uses many of the aspects of the pupil
tracking system described above, retinal OCT images are acquired
through multiple points in the pupil. An automated movement of the
OCT beam relative to the patient's pupil allows acquisitions at
measurable, and preferably pre-determined, positions in the
patient's pupil. The movement may be achieved by various means,
such as moving the patient's eye relative to the instrument, by
moving the instrument relative to the patient's eye, by translating
a portion of the instrument like an optical subsystem, or by moving
the beam such as with a tilted block of glass that is moved into
and out of the path. A manual adjustment can be regulated or guided
by typical physical constraints such as detent positions or a
hand--operated lever with pre-set motion range. The relative angle
of incidence can be determined from the ratio of distance moved in
the pupil divided by a typical focal length of the eye, or by
accounting for the individual eye length obtained by a convenient
method, such as measured axial length or inferred from correlation
of refractive error to eye length. The actual movement relative to
the patient pupil can be approximated by a measurement of the
motion of the patient's head or of the instrument. In typical
ophthalmic OCT systems, the illumination and collection are usually
co-aligned, for example using a common fiber. In this case the
angles of incidence and collection are changed together. In a
system where the illumination and collection are not co-aligned,
the angles can be varied independently of each other using methods
obvious to those skilled in the art. Furthermore, a plurality of
illumination or collection paths may be implemented for
simultaneous measurements. The implementation is described herein
assuming co-alignment of illumination and collection for clarity of
description and because this is the most common configuration;
nevertheless, co-alignment is not required.
[0079] When multiple images with multiple angles of incidence are
obtained, the images can be compared with each other by several
methods, such as image-based registration of the images followed by
creation of difference images or ratio images. Alternatively the
scattering profile as a function of depth can be extracted at
matching points on the image for comparison. In any case,
comparison may include pre-processing of the data, such as
background subtraction, gain adjustment (for example to compensate
for variations in overall brightness between scans), filtering and
averaging to reduce noise, and the creation of summary
parameters.
[0080] The scattering signal varies with the angle of incidence, so
algorithms which segment layers can use information about the local
angle of incidence of one or more layers to correctly identify
layer boundaries. This is illustrated, for example, in the region
generally described as being between the retinal pigment epithelium
and the outer plexiform layer (RPE and OPL). In this region, the
boundaries between bright and dark layers depend on the angle of
incidence. As described above, as the angle of incidence changes,
the apparent tilt of the retina in the B-scan changes.
[0081] FIGS. 13(a) and (b) show two OCT images. They are both taken
at the same location, but with different angles of incidence to the
retina. FIG. 13(a) is captured with the scan beam about 5-10
degrees from one side of the normal, and FIG. 13(b) is captured
with the scan beam at an angle with a similar magnitude but from
the opposite side of the normal. The two images have been
registered to each other by measuring and then correcting for
differences in the tilt and relative position of tissue in the
B-scans. The scattering between "RPE" and "OPL" increases on the
side of the retina that appears farther from the incident light
than the fovea (left side in FIG. 13(a) denoted by arrow 1301 and
right side in FIG. 13(b) denoted by arrow 1302). On the opposite
side of the fovea, the scattering is reduced and appears to come
from a thinner layer (arrows 1303 and 1304). Thus, it is the angle
of incidence, not an asymmetry in the tissue, which causes the
effect. As described by Lujan et al, this layer of increased
scattering is attributed to Henle's fiber layer (HFL). In this
region, an algorithm will attribute the boundary between bright and
dark bands to a transition between one pair of layers if the angle
of incidence is such that the region appears thicker and to a
transition between another pair of layers if the angle of incidence
is such that the region appears thinner. The algorithm can obtain
this information about the relative angle of incidence from various
means, including information about the position of the OCT scan
beam in the pupil or by the tilt of the retina in the B-scan as
measured either globally or locally. In the case of retinal
pathology where local tissue layers are distorted and their
orientation is substantially different from the bulk of the retina,
a local measurement of the tilt may be more appropriate.
[0082] In some cases, the layers of interest can be observed at all
angles, even if the gradients in intensity are different depending
on the angle. In other cases, the layer of interest may not be
differentiated when imaged at a given incident angle. In FIG. 13,
there is a layer above the RPE that is apparent in 13(a), but not
seen in 13(b) as illustrated by arrow 1305. This layer represents
the interdigitation of the RPE with the inner segments of the
photoreceptors. If this layer is of interest, it is necessary to
find angles at which it can be imaged. Alternately, the boundaries
of the HFL can be seen in both 13(a) and 13(b), although the
intensity characteristics are very different. To segment this layer
it might be sufficient to know the local angle of incidence
relative to the fibers. Finally, when the angle of incidence and
its effect on tissue reflectivity is known, then the reflectivity
may become a useful aspect of anatomy or pathology subject to
measurement. That is, if the reflectivity is variable and depends
on an unknown angle of incidence, it is difficult to tell if a
tissue is poorly imaged or absent. If factors that depend on image
setup have been controlled for, the reflectivity may become a
useful indicator of health or disease of a given tissue. Examples
include detecting glaucomatous damage by evaluating reduced
reflectivity of the retinal nerve fiber layer, using the
reflectivity of the contents of pigment epithelial detachments to
determine the nature or cause of the detachment, and using the
reflectivity observed in the outer nuclear layer to evaluate
disruptions in the retina.
[0083] The OCT images can be obtained with a variety of optical
configurations, such as dedicated OCT scanner, an SLO device,
through a surgical microscope, or a slit-lamp mounted OCT among
others. The above text clearly states that the beam should be moved
relative to the pupil to change the angle of incidence. FIG. 14
further clarifies this by showing one example approach. Scan beam
33 is moved relative to eye. In this embodiment, the measuring
module 30, which could be for example, just part of scan head,
entire instrument, or some subset of the instrument that controls
position of the scan beam, is translated along direction 31 so that
beam moves relative to the eye, shown here as the approximate axis
of the eye 37 to scan the posterior pole 34. Entry points are
limited by the pupil boundary 35. This can also be done in the
plane 32 perpendicular to the drawing plane. An example of
determining the relative angle of incidence from the beam position
is to detect the position of the beam 33 relative to the pupil 35
by means such as a CCD camera. The movement does not need to be a
pure translation of measuring module 30 as long as the position of
the beam 33 relative to the pupil boundary 35 is changed. If the
distance from measuring module 30 to pupil boundary 35 is
sufficiently large then the position of the beam at the pupil
boundary 35 can be changed with only minor changes to the angle of
incidence at the retina by rotating measuring module 30 to move the
position of the beam in the pupil plane.
[0084] This method has been used to make such measurements with a
Cirrus OCT (Carl Zeiss Meditec, Inc. Dublin, Calif.). Images have
been analyzed in several ways, both by image registration and
comparison of intensity profiles. FIG. 15 shows a plot of intensity
profiles from two separate B-scans taken from the same region of
the retina but with angles of incidence that vary by approximately
15 degrees based on calculations of beam position in the pupil as
described above. Features commonly referred to as the inner
limiting membrane (ILM) 1, and retinal pigment epithelium (RPE)
layer 2 are indicated in the plot. The scattering intensity is
different between the two scans due to differences in the angle of
incidence of the scanning beam on the tissue. For example,
scattering intensity is higher at point 3.
[0085] As described above, the intensity between images can also be
compared, for example, by subtracting the two profiles from each
other as shown in FIG. 16. Locations 21, 22 and 23 correspond to
locations 1, 2, and 3, respectively, in FIG. 15. The difference
between the two profiles is caused by measurement noise,
registration errors, and repeatable differences due to different
angles of incidence. For example, the existence of region 23 is due
to a difference in the angles of incidence. Using this difference
as a contrast mechanism, the thickness 24 of the tissue whose
contrast changes can be measured.
[0086] Similar analyses can be performed on entire OCT B-scans.
FIG. 17 shows the resulting difference image generated by
subtracting the two scans shown in FIGS. 13(a) and (b), one from
the other. The difference image highlights differences in
scattering due to angle of incidence of the OCT scan as indicated
by arrow 1701.
[0087] The difference image can be displayed in variations, such as
color. For black and white viewing, the negative image, formed by
subtracting the images in the opposite order can be useful as well.
FIG. 18 shows how regions that are difficult to see in FIG. 17 can
be visualized more clearly, one example of which is indicated by
arrow 1702.
[0088] The preferred embodiment encompasses an automated process
whereby OCT images are collected at multiple angles of incidence,
the images are registered to each other, and processed either by
subtraction of B-scans or intensity distributions to identify and
determine the thickness of specific layers with angle dependent
intensity.
[0089] Opacity Mapping
[0090] An additional aspect of the present invention is the ability
to provide an opacity map of the pupil of a patient to a clinician
that highlights regions of opacity such as cataracts and further
give insights into the "denseness" of the opacity
[0091] The main components of this invention are an imaging means
to obtain an image of the eye, a processing unit to segment the
boundaries of the pupil and a unit to track the gaze of the eye and
a measurement unit that measures some property of the eye by
sending an optical beam through the pupil. The invention is general
and can work with any type of pupil segmentation and gaze
tracking.
[0092] As the first step, the boundaries of the pupil are
segmented. Using the segmentation of the pupil, it is possible to
make the measurement beam pass through different points on the
pupil automatically. The resulting signals can be analyzed to find
the quality of the measurement signal. For example, in an OCT
system, the quality could be the signal strength of the acquired
OCT A-Scan or B-Scan. The quality of the measurement signal is
usually inversely related to the opacity. The beam entry position
can be varied over a grid and a mapping of the opacity can be
obtained since the quality of the measurement signal corresponds to
the opacity at the corresponding beam entry position. One example
of such a mapping is shown in FIG. 19. Darker shading as visible in
the top right part of the image 1901 means there is more
opacity.
[0093] Although various embodiments that incorporate the teachings
of the present invention have been shown and described in detail
herein, those skilled in the art can readily devise many other
varied embodiments that still incorporate these teachings.
[0094] The following references are hereby incorporated by
reference:
[0095] Patent Documents
[0096] US Patent Publication No. 2005/0024586 Teiwes et al.
"Multidimensional eye tracking and position measurement system for
diagnosis and treatment of the eye"
[0097] US Patent Publication No. 2007/0291277 Everett et al.
"Spectral domain optical coherence tomography system"
[0098] U.S. Pat. No. 7,805,009 Everett et al. "Method and apparatus
for measuring motion of a subject using a series of partial images
from an imaging subject"
[0099] U.S. patent application Ser. No. 13/433,127, filed Mar. 28,
2012, Iyer et al. "Systems and methods for efficiently obtaining
measurements of the eye using tracking"
[0100] Non-Patent Literature
[0101] Lujan et al. "Henle's Fiber layer revealed using spectral
domain optical coherence tomography" ARVO abstract #1201 2010.
[0102] Lujan, et al. "Revealing Henle's Fiber Layer using Spectral
Domain Optical Coherence Tomography". Investigative Ophthalmology
& Visual Science 52(3) March 2011 1486-1492.
[0103] Liao et al. "Robust Pupil Detection for Gaze-Based User
Interface" EGIHMI '10 Proceedings of the 2010 Workshop on Eye Gaze
in Intelligent Human Machine Interaction.
[0104] Zhu et al. "Robust Pupil Detection using a Curvature
Algorithm" Computer Methods and Programs in Biomedicine 59 (1999)
145-157.
[0105] Li et al. "Starburst: A hybrid algorithm for video-based eye
tracking combining feature-based and model-based approaches" Vision
for Human-Computer Interaction Workshop (in conjunction with CVPR),
2005.
[0106] Leitgeb et al., "Ultrahigh resolution Fourier domain optical
coherence tomography," Optics Express 12(10):2156 2004
[0107] Choma et al. (2003). "Sensitivity advantage of swept source
and Fourier domain optical coherence tomography." Optics Express
11(18): 2183-2189
* * * * *